// CHECK-LABEL: func @tfAssertTrue
func.func @tfAssertTrue(%arg0: tensor<1x1x6x2xf32>) {
  %t = arith.constant dense<true> : tensor<i1>
  // CHECK-NOT: tf.Assert
  "tf.Assert"(%t, %arg0) {summarize = 3} : (tensor<i1>, tensor<1x1x6x2xf32>) -> ()
  func.return
}

// CHECK-LABEL: func @tfAssertFalse
func.func @tfAssertFalse(%arg0: tensor<1x1x6x2xf32>) {
  %f = arith.constant dense<false> : tensor<i1>
  // CHECK: tf.Assert

func.func @testPReluValidBroadcast(%arg0: tensor<19x7x12x14xf32>, %arg1: tensor<1x1x14xf32>) -> tensor<19x7x12x14xf32> {
  %0 = "tfl.prelu"(%arg0, %arg1) : (tensor<19x7x12x14xf32>, tensor<1x1x14xf32>) -> tensor<19x7x12x14xf32>
  func.return %0 : tensor<19x7x12x14xf32>
}

// -----

func.func @testPReluValidFullBroadcast(%arg0: tensor<7x8x9x10xf32>, %arg1: tensor<1x1x1xf32>) -> tensor<7x8x9x10xf32> {

  func.return %0 : tensor<1x10x10x32xi32>

// CHECK-LABEL: biasAddInt
// CHECK:  "tf.BiasAdd"(%arg0, %arg1)
}

func.func @squeezeAndReshape(%arg0: tensor<1x1x10xf32>, %arg1: tensor<?x10xf32>) -> i32 {
  %0 = "tf.Squeeze"(%arg0) {squeeze_dims = [0]} : (tensor<1x1x10xf32>) -> tensor<1x10xf32>
  %1 = "tf.Squeeze"(%arg1) : (tensor<?x10xf32>) -> tensor<*xf32>
  %2 = "tf.Const"() { value = dense<[2, 5]> : tensor<2xi32> } : () -> tensor<2xi32>

    %cst_5 = arith.constant dense<512> : tensor<i32>
    %19 = "tf.Pack"(%18, %cst_5) {N = 2 : i64, T = i32, axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32>
    // CHECK: -> tensor<1x512xf32>
    %40 = "tf.Reshape"(%39, %19) {T = f32, Tshape = i32, device = ""} : (tensor<1x4x4x32xf32>, tensor<2xi32>) -> tensor<?x?xf32>
   func.return
  }

  // CHECK-LABEL: func @shape_partial_eval